PhD Student in Cyber-Physical Systems (CPS)

PhD Student in Cyber-Physical Systems (CPS)

Norrbottens län, Lulea

Luleå University of Technology is in strong growth with world-leading competence in several research areas. We shape the future through innovative education and ground-breaking research results, and based on the Arctic region, we create global social benefit. Our scientific and artistic research and education are conducted in close collaboration with international, national and regional companies, public actors and leading universities. Luleå University of Technology has a total turnover of SEK 1.9 billion per year. We currently have 1,840 employees and 17,670 students.

In the coming years, multi-billion investments will be made in large projects in Northern Sweden to create a fossil-free society both nationally and globally. Luleå University of Technology is involved in several of these cutting-edge research projects and in the societal transformation that they entail. We offer a broad range of courses and study programmes to match the skills in demand. We hope that you will help us to build the sustainable companies and societies of the future.

The EISLAB division of the Department of Computer Science, Electrical and Space Engineering conducts research within Cyber-Physical Systems, Electronic Systems, and Machine Learning. The research at Cyber-Physical Systems is conducted in close collaboration with industries such as Bosch, Ericsson, Volvo, Infineon, Boliden, LKAB, SKF, and leading international universities. A major result is the Eclipse Arrowhead, an open-source software framework for industrial automation widely supported by European industry. 

Subject description 
Cyber-Physical Systems (CPS) focuses on integrated software and application architectures with implementations of massively distributed embedded systems that interact with each other and their environment to enable secure, goal-driven, autonomous, and evolvable solutions. 

Project description
You will be working as part of a team of researchers on a European project. As a main topic, you will perform your research in one of these areas: 
-Data model translation, to enable the automatization of the engineering process. 
-Machine learning-based code generation for autonomous translation of payload data semantics. 
-Dictionary learning and algorithms for translation between major data modeling languages. 
-Model-based System Engineering (UML, SysML, metamodels) usage to model the major data modeling languages. 

The project aims to further digitalize the European industry, where EISLAB/CPS will be responsible for the CPS intelligence, IoT, and SoS automation architecture as well as the use of AI and Machine Learning (ML). Targeted results include academic papers and contributions with open-source code for the Eclipse Arrowhead. Projects typically involve working with both academic and industrial partners in Europe. Hence, collaboration with the software and automation industry is a key factor for the success of these projects. In this, you will work closely with other LTU researchers and doctoral students. 

As a PhD student, you work towards a Doctoral degree as the final goal. The work will address the objectives of the Higher Education Ordinance. Most of your time will be devoted to working on research projects in which you will develop proofs-of-concept to experimentally evaluate and explore aspects of industrial software systems and components. You will communicate your results at international conferences and in scientific journals. 

To support your dissertation work, you will take courses including third-cycle studies introduction, generic courses for the LTU PhD program, specially designed courses, etc. Your research and coursework will be planned and recorded in your individual study plan throughout your progress. Teaching and other duties at the division or department exist for graduate students, which are limited to a maximum of one year of the total five-year period. 

We are looking for You - a talented, analytical, and motivated colleague who, both alone and in collaboration with others, can carry out advanced research in our research group. The necessary background for applicants is a master’s degree in preferably Computer Science. Also, Electrical Engineering, Engineering Physics, or equivalent will be considered. We also welcome applicants with expected graduation in such a degree in 2024, August at the latest. 

The applicant must be proficient in Computer Science. Previous experience working with SOA, IoT, SysML, ML, CPS, and/or SoS is valuable but not a requirement. The applicant must also possess good programming skills, including software design, and basic programming concepts as well as experience in Java programming or similar. Fluency in oral and written communication in English is a requirement. 

For further information about a specific subject see;
 General curricula for the Board of the faculty of science and technology 

Further information 
Employment as a PhD student is limited to 4 years, with an extension of a maximum of one year for teaching and other department duties. Placement: Luleå. Starting: Autumn 2024. 

For further information about the position, please contact Cristina Paniagua, +46 (0)920 493858

Union representatives:
SACO-S Kjell Johansson (+46)920-49 1529  
OFR-S Lars Frisk, 0920-49 1792 

In the case of different interpretations of the English and Swedish versions of this announcement, the English version takes precedence. 

We prefer that you apply for this position by clicking on the apply button below. The application should include a CV, personal letter and copies of verified diplomas from high school and universities. Mark your application with the reference number below. Your application, including diplomas, must be written in English or Swedish. 

Reference number: 2107-2024 
Last day of application: August 4 2024

Luleå Tekniska Universitet

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Deadline: 2024-08-04
Location: Sweden, Luleå
Categories: Computer Sciences, Cyber-Physical Systems, Electrical Engineering, Electronics, Machine Learning, PhD,


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